Today, companies and data centers are moving towards cloud and serverless storage systems instead of traditional file systems. As a result of such a transition, allocating sufficient resources to users and parties to satisfy their service level demands has become crucial in cloud storage. In cloud storage, the schedulability of system components and requests is of great importance to achieving QoS goals. However, the bufferbloat phenomenon in storage backends impacts the schedulability of the system. In a storage server, bufferbloat happens when the server submits all requests immediately to the storage backend due to a large buffer in the backend. In recent decades, many studies have focused on the bufferbloat as a latency problem. Nevertheless, none of these works investigate the impact of bufferbloat on the schedulability of the system. In this paper, we demonstrate that the bufferbloat impacts scheduling and performance isolation and identify utilizing admission control in the storage backend as an easy-to-adopt solution to mitigate bufferbloat. Moreover, we show that traditional static admission controls are inadequate in the face of dynamic workloads in cloud environments. Finally, we propose SlowFast CoDel, an adaptive admission control, as a starting point for developing adaptive admission control mechanisms to mitigate bufferbloat in cloud storage.

翻译：当今，企业和数据中心正从传统文件系统向云存储和无服务器存储系统迁移。这种转变使得为用户和各方分配充足资源以满足其服务级别需求在云存储中变得至关重要。在云存储中，系统组件和请求的可调度性对于实现服务质量目标具有重要意义。然而，存储后端中的缓冲膨胀现象会影响系统的可调度性。在存储服务器中，当由于后端缓冲区过大而导致服务器将所有请求立即提交至存储后端时，便会发生缓冲膨胀。近几十年来，许多研究将缓冲膨胀视为延迟问题。然而，这些工作均未探讨缓冲膨胀对系统可调度性的影响。本文证明了缓冲膨胀会影响调度和性能隔离，并指出在存储后端利用准入控制是缓解缓冲膨胀的一种易于实施的解决方案。此外，我们揭示了传统静态准入控制在云环境的动态工作负载面前存在不足。最后，我们提出自适应准入控制机制SlowFast CoDel，作为开发缓解云存储中缓冲膨胀的自适应准入控制机制的起点。